Frontend
Features
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Description
The PerceptiLabs Operator creates and maintain PerceptiLabs, a visual modeling tool for machine learning at warp speed.
PerceptiLabs visual modeling tool provides a GUI for building, training, and assessing your models, while also enabling deeper development with code. You get faster iterations and better explainability of the results.
For more information visit perceptilabs.com.
Features
Fast modeling
Make changes, debug, and tune your model through the GUI or custom code editor where every component/layer is re-programmable. Choose from multiple neural network models as well as classical AI methods.
Transparency of Model Performance and Results
Get instant feedback into your model’s performance through the visualization of the architecture, to better review and understand the results. See real-time analytics in every operation and variable, and granular previews of output from each model component.
Flexibility
Customize your environment and statistics dashboard. Use high-level abstractions or low-level code. Choose a local or cloud-based version. Execute any custom Python code or export a fully-trained TensorFlow model to perform inference in your projects.
Products using this container
Image specifications
The following information was extracted from the dockerfile and other sources.
| Canonical image ID | Frontend |
| Summary | This is the free version of the frontend of our modeling platform v1. |
| Description | Python 3.6 available as container is a base platform for building and running various Python 3.6 applications and frameworks. Python is an easy to learn, powerful programming language. It has efficient high-level data structures and a simple but effective approach to object-oriented programming. Python's elegant syntax and dynamic typing, together with its interpreted nature, make it an ideal language for scripting and rapid application development in many areas on most platforms. |
| Provider | PerceptiLabs AB |
| Maintainer | SoftwareCollections.org <sclorg@redhat.com> |
| Repository name | PerceptiLabs-Modeling-Web-app |
| Image version | 0.11.5 |
| Architecture | amd64 |
| Usage | s2i build https://github.com/sclorg/s2i-python-container.git --context-dir=3.6/test/setup-test-app/ ubi8/python-36 python-sample-app |
| Exposed ports | "8080/tcp" |
| User | root |
| Working directory | /opt/app-root/src |
Audit & compliance status
The following evidence verifies the image's security and build process compliance with mandated internal standards.
| Security audit date | 4/15/2024, 3:00:00 PM |
| Container certification |
Registry tokens
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Using Podman login
Run the following command, then enter your registry token credentials when prompted by the terminal.
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Image identifiers
Red Hat login
Use the following instructions to get images from a Red Hat container registry using your Red Hat login.
Using Podman login
Run the following command, then enter your login credentials when prompted by the terminal.
Pull the image
